Abstract A key feature of highly aggressive cancers is their invasiveness, where transformed cells disseminate by crawling through the local micro-environment, ultimately causing death as the tumor invades and metastasizes. If these processes of cell motility could be suppressed, it would potentially extend lifespan and increase the potential effectiveness for local and global therapeutic treatments. However, we do not adequately understand the mechanical and chemical basis of cancer cell migration in complex and mechanically challenging microenvironments. The goal of this project is to develop and use a mathematical/computational model that will allow us to simulate cancer migration on a computer, and, in the longer-term, perform virtual in silico drug screening. Specifically, during this project we will mechanically parameterize glioblastoma (GBM) and pancreatic ductal adenocarcinoma (PDA) tumor cell migration so that patient outcomes can be predicted and new therapeutic strategies identified. Employing physical modeling for whole cell model migration, we have developed a ?Cell Migration Simulator, v1.0,? (CMS1.0) to capture fundamental intracellular and extracellular mechanical processes regulating cell migration. Here, CMS1.0 will be used to 1) mechanically parameterize tumor heterogeneity, 2) bias immune-cancer cell interaction away from suppression and toward killing, and 3) elucidate proto-oncogene mechanism. Finally, we will also further develop the CMS1.0 to include more explicit F-actin dynamics, cell mechanics, and environmental fiber mechanics. In the process, we will build a physical sciences-based, patient-oriented approach toward understanding and controlling a key driver of cancer progression, cell migration. Thus, the project will establish the quantitative framework necessary to develop a model-driven approach to brain and pancreatic cancer invasion, so that therapies can be designed and engineered for better, more predictable outcomes.